轴承故障诊断通过一步步的小规范化与适应性小字典
Lichao Yu1, Chenglong Wang1, Fanghong Zhang2
1School of Aerospace Engineering, Xiamen University, Xiamen 361102, China.
Sensors (Basel, Switzerland)
|April 27, 2024
概括
一种新的逐步稀疏调节 (SSR) 方法通过准确地从噪声中提取信号来改善轴承故障诊断. 这种技术提高了稀疏性和数据保真性,以便更精确地检测故障.
科学领域:
- 机械工程 机械工程
- 信号处理 信号处理
- 状态监控 状态监控
背景情况:
- 振动监测对于轴承故障诊断至关重要.
- 基于稀疏性约束的规范化有效地从噪声信号中提取了瞬态信号.
- 传统方法面临的是稀疏性和数据保真性之间的权衡.
研究的目的:
- 为了解决传统稀疏规范化方法的局限性.
- 提出一种新的逐步稀疏规范化 (SSR) 方法.
- 为了提高轴承故障诊断的准确性.
主要方法:
- 模拟轴承故障诊断作为一个多参数优化问题.
- 引入了一种逐步稀疏规范化 (SSR) 方法,配备了一个自适应稀疏字典.
- 实施了稀疏性增强和忠实性增强的优化步骤.
主要成果:
- 通过SSR方法,可自适应地确定时间指数和原子数.
- 通过删除正规化项,实现了高精度的重建幅度.
- 在各种噪音条件下,与其他稀疏调整方法相比,证明了更高的重建精度.
结论:
- 拟议的SSR方法克服了稀疏性和数据忠实性之间的权衡.
- SSR为轴承故障诊断提供了更准确的结果.
- 这种方法为从噪音振动信号中提取重复的短暂物提供了增强的能力.
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